Vegetation Phenology Metrics Derived from Temporally Smoothed and Gap-Filled MODIS Data

A set of phenology metrics have been estimated based on temporally smoothed and spatially gap-filled Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices (VI) over the North American continent. The phenology algorithm has been applied to three MODIS vegetation indices: Leaf Area Index (LAI), Normalized Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI). The spatial coverage of this phenology data is more complete than other remotely sensed data based phenology products. This is because of the quality of the smoothed and gap-filled MODIS data that was produced using an enhanced version of the TIMESAT algorithm. In this paper, we review the enhanced TIMESAT algorithm and related smoothing, gap filling and phenology algorithm, and compare the phenology metrics estimated from NDVI and EVI. Our results show differences in phenology inferred from EVI versus NDVI. The magnitude of the difference depends on the land cover type and could be used to improve the land cover classification accuracy.